Open AccessA METHOD FOR THERMAL HISTORY PREDICTION DURING ADDITIVE MANUFACTURING USING FAR-FIELD TEMPERATURE MEASUREMENTS
Author(s) -
R. Rangarajan,
A. E. Segall,
Richard P. Martukanitz,
Frederick Lia
Publication year - 2019
Publication title -
journal of modern mechanical engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2409-9848
DOI - 10.31875/2409-9848.2019.06.4
Subject(s) - thermal , radiative transfer , materials science , computer science , offset (computer science) , boundary layer , mechanical engineering , residual , process engineering , process (computing) , mechanics , algorithm , optics , thermodynamics , engineering , physics , programming language , operating system
Directed Energy Deposition is a near net-shape, additive manufacturing process that uses high-energy lasers for powder melting and consolidation. While a detailed knowledge of the thermal histories of the process can help understand and ultimately predict the resulting microstructure, residual-stresses, and/or material properties of the component, experimental limitations usually restrict all temperature measurements to far-field locations. When fixed, these measurements become increasingly removed from the laser/material interactions as the build process unfolds. To help offset this limitation, a relatively straightforward method using finite-elements and a fixed far-field measurement was developed that considers experimental processing conditions such as a moving heat source and relevant (and evolving) boundary conditions to generate more complete thermal histories. In essence, an inverse problem was iteratively solved using a direct computational approach. Once validated, the model was then used over multiple depositions with the outcome discussed relative to the agreement and disparities in peak temperatures, heating, and cooling rates. The increasing importance of the growing surface area and evolving radiative and convective boundary conditions with each layer was clearly demonstrated